Langflow: review, pricing, security and alternatives

What Langflow does

Langflow belongs to the automation family: platforms, often visual, that chain steps, apps and models into workflows with or without an agent. On our grid it ranks #1 of the 26 projects of this family listed in the directory.

You use it from: web app and API. Usable models: Claude (Anthropic), GPT (OpenAI), Gemini (Google), local models (Ollama, llama.cpp, vLLM…), and any OpenAI-compatible model. It can run on your own machine or server.

Who is Langflow for?

It is for teams that want to connect their tools (CRM, e-mail, spreadsheets) and hand the AI the steps that require reading or deciding. Typical tasks people give it:

• qualify incoming requests and route them
• extract data from documents into a spreadsheet
• generate periodic reports

It is a good candidate if you prefer doing everything in a browser, with no install, your data must stay on your machines, and you want the option of a local model, with no API fees.

Access and human control

Its documentation does not detail the access granted to the agent: check the settings before connecting it to your accounts.

We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.

Langflow pricing

The code is free, under the MIT licence.

Getting started with Langflow

1. Install it: the project ships as a Python package (install with pip or uv). The exact command is in the repository README.
2. Pick the model: an API key from a provider, or a local model if your machine has enough graphics memory (the VRAM calculator tells you).
3. Give it a first playground with nothing at stake: a test folder, a secondary account or a throwaway project. Only open your real accounts once you have seen how it behaves.
4. Give it a short, checkable task, review the result and its action log, then raise the difficulty step by step.

Security: risk level

A workflow runs unattended: limit the credentials it holds and log what it sends.

Three habits: least privilege (minimal rights, dedicated keys), human approval for irreversible actions, a sandbox for code execution. The AI agent security check reviews your setup in a few minutes.

Project activity and releases

Created on February 8, 2023, the langflow-ai/langflow repository has 155,979 stars, 10,240 forks and 206 open issues, with 19,550 commits in total. It received changes this month.

Over the last 52 weeks: 4,979 commits, an average of 95.8 per week.

316 releases in total; 30 in the last twelve months. Latest release: v1.13.0, on October 22, 2026.

Langflow vs other automation

GitHub stars of the best-rated open-source projects in the automation family. Stars measure attention, not quality: a heavily promoted project collects them fast, a specialised tool will have few.

Langflow and other automation at a glance

The 7 best-ranked agents in the same family, 7 of them open source. The score out of 100 only applies to open-source projects; for proprietary services we show the published entry price. A dash marks information the documentation does not state.

How we rated it

Score: 93/100, computed only from public, verifiable data, with no subjective testing or partnership:

• Adoption 38/40: 155,979 stars on a log scale (40 points from about 200,000).
• Activity 30/30: last commit less than a month ago, 26 releases in six months, 4,979 commits in a year.
• Framework 25/30: licence, default human approval, self-hosting, model choice and documentation site.

The score does not say whether the agent will succeed at your tasks: it measures how solid the project is. The full grid is on the method page.